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New White Paper: Who is Doing Computational Social Science?

September 29, 2016

Survey Results Explore Trends in Big Data Research among Social Scientists

Los Angeles, CA (September 29, 2015) While the “big data revolution” promises to ask and answer important questions about our social world, it requires new analytical practices, cross-disciplinary collaboration, and the right tools and training to tackle the vast amounts of digital information available to researchers. In response to this challenge, new research practices are being developed by the emerging field of “computational social science.” And these new tools bring their own questions: Who is currently engaging in this type of research? What obstacles do these researchers face? And what hurdles discourage newcomers to the field? A new SAGE Publishing white paper out today titled “Who is Doing Computational Social Science? Trends in Big Data Research,” answers these questions and more.

SAGE Publishing surveyed social scientists across the globe in May, 2016 in order to better understand the challenges and opportunities that result from the increased availability of “big data.” The findings from the 9,412 responses revealed the following:

33% of respondents said they had been involved in big data research of some kind and 49% said they were “definitely planning on doing so in the future” or “might do so in the future.” 60% of respondents who are doing big data research had done so within the last 12 months.

55% of respondents who have done big data research have used admin data, 29% have done research using some kind of social media data, and 23% have used commercial data in their research.

While 79% of those doing big data research have collaborated with other academics, the majority of researchers had not shared the code or software they developed with other researchers.

Of the biggest challenges facing those who do big data research, 42% reported getting funding and 32% reported access to data as a “big problem.”

Of those teaching big data analytics or data science methods, the biggest problem named was levels of programming and statistical knowledge of students.

Of those wishing to enter big data research, the biggest problems named were finding collaborators with the right skills and not enough time to learn a new skill.

"We had a great response to our survey with over 9,000 people reaching the end, which shows the level of interest there is among social science academics and professionals around big data. While some respondents cautioned that big data was overhyped and warned of issues around data quality, many other respondents expressed a wish for more training to help them engage in this type of research in the future. The findings of the survey help us to understand the challenges facing researchers in the social sciences who want to work with large datasets or teach students how to do so, and we hope, through our publishing, product development, and advocacy work, to help relieve some of these pain points."

“Today’s social scientists are addressing the same ‘wicked’ social issues that their predecessors have explored for decades – educational development, health reform, inequality, the growth of democracy, to name just a few – but now with the benefits of vast amounts of data waiting to be analyzed. The findings from this survey reveal that there is an appetite to engage with data at an accelerated rate among social scientists, but that unique challenges persist related to such issues as interdisciplinary connections (as I discussed in response to the Edge Question 2016), research design training, and access. As a social science publisher that has been innovating in social science methods for more than four decades, SAGE Publishing is dedicated to creating new ways to help these researchers and their successors in this journey.”

Find out more by reading the full white paper, written by Katie Metzler, Publisher for SAGE Research Methods, David A. Kim, from Stanford University’s Department of Medicine, Nick Allum, Professor of Sociology and Research Methodology at the University of Essex, and Angella Denman, also at the University of Essex.

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